Combining context-awareness with computerized decision support systems ... The PROPHET system provides a good example of the implementation.
Congrès annuel 2008 de la SCGC CSCE 2008 Annual Conference
Québec, QC 10 au 13 juin 2008 / June 10-13, 2008
APPLICATION OF CONTEXT-AWARE COMPUTING TO CONSTRUCTION FEILD WORK SangHyun Lee1 and Osama Mohsen2 1 Assistant Professor, Hole School of Construction Engineering, Department of Civil and Environmental Engineering, University of Alberta, Edmonton, Alberta, Canada 2 Graduate Student, Hole School of Construction Engineering, Department of Civil and Environmental Engineering, University of Alberta, Edmonton, Alberta, Canada
ABSTRACT: Construction projects by nature are highly complex and dynamic, and the amount of information involved is considerable. As such, accessing the right information at the right time can largely serve to facilitate the completion of the project within time and budgetary constraints. Focusing on this issue, intelligent information delivery at dynamic construction jobsites is sought using a process of Context Aware Computing which takes into account context (e.g., user’s location and profile) for intelligent human-computer interaction. Throughout this paper, the authors will review the current research of Context Aware Computing, particularly with respect to construction, and propose a taxonomy of context in order to capture the dynamic nature of construction operations. Also, possible implementation and application scenarios will be discussed.
1. INTRODUCTION Automation in construction sites can take on a number of different aspects and dimensions. One manifestation of automation in construction sites is to deliver relevant information intelligently to the user on an as-needed basis. In other words, taking into account the dynamic nature of construction, accessing the right information at the right time enables construction workers to reduce the time and effort needed to maintain a current knowledge of changing information. However, the existing practice in construction industry involves providing workers with information that for the most part does not account for the changing conditions of the worksite, such as location of the user, current operation, and the time of performing tasks. The dynamic nature of the construction environment often entails information overload and large volumes of data. Thus, it becomes essential to filter and classify this enormous amount of data so that only relevant information is delivered, and at the appropriate time. Delivering relevant information to the interested user at the right time depends greatly on the context of the work being performed. Here, context has been defined as any data used to characterize an entity, whether this entity is a person, location, or equipment (Singhvi and Terk, 2003). Context can include identity of users, locations, time, activities in which a user is involved, as well as the type and capability of the computing device. In other words, in this research context refers not only to the location of users or objects, but all aspects of the physical or social situation, such as who the user is, what activities he or she is engaged in, and what objects are nearby.
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In an effort to utilize these contexts for intelligent information delivery, Context Aware Computing has been introduced to the construction domain (Singhvi and Terk, 2003; Aziz and Anumba, 2006). Context Aware Computing (CAC) is defined as the use of environmental characteristics such as the user’s location, time, identity, profile, and activity in order to inform the computing device such that it may provide information to the user which is relevant to the current context (Burrel et al., 2002). CAC relies upon intelligent methods to deliver the necessary information at the right time (Anumba and Aziz, 2006). Although some of the captured information is considered irrelevant or of minor importance to construction activities, capturing and processing these data intelligently can improve productivity and efficiency of the overall construction process. Combining context-awareness with computerized decision support systems can facilitate on-site collaboration and communication as well as better decision making capabilities. The Objective of this paper is to provide an overview of the current practice in construction regarding the utilization of CAC as well as exploring possible future avenues and applications of this technology within different construction activities and scenarios. This paper first presents a brief literature review of CAC emphasizing the application of context-aware services in construction environment. Then, construction context taxonomy is proposed to capture the dynamic nature of construction, and several possible scenarios are discussed.
2. APPLICATIONS OF CONTEXT AWARE COMPUTING Context Aware Computing (CAC) has been applied to a large number of applications, including museums (Fleck et al., 2002), route planning (Marmasse et al., 2002), tourism (laukkanen et al., 2002), and medicine (Bardram, 2004), focusing on intelligent information delivery. For example, a large amount of documents, schemas, and charts in medical work are structured according to the specific work context (Bardram, 2004). In this work, the patient's bed has an integrated computer system with several RFID sensors that can identify the patient, the medical staff, and various medical equipments. When the doctor arrives, the bed is able to log in the doctor and display all relevant medical records and medicine schemas from a centralized system. Another application of CAC has been developed and tested at a college campus using a location-sensitive service (Burrell et al., 2002). The goal here had been to provide prospective students visiting the campus with information about the different ongoing activities as well as general information about the new environment. The system allows the users to annotate the physical space with knowledge and comments. Visitors to the campus can also annotate space with questions and thoughts as well as reading comments made by people who know about the campus. In this work, the idea of “social maps” has been investigated as a means to obtaining knowledge and behavior from other users. These maps would create an information map of user behavior and comments layered on top of the physical map, making these activities visible for some time (Burrell et al., 2002). With respect to construction, Singhvi and Terk (2003) have proposed a contextual information system called PROPHET, designed to deliver up-to-date contextual data and services at construction sites. This system allows users to track current resource requirements and obtain access to information and services related to their context. In the proposed system, the basic elements of context are: identity of the user, temporal information, location, and community; these elements are referred to as the raw context. In addition to raw context is the derived context, which characterizes the environment and is generated from project information (Singhvi and Terk, 2003). The hardware infrastructure for this system consists of a wireless network, several server machines, and a client application running on handheld devices. Determination of outdoor locations is accomplished using GPS, whereas indoor location is determined using a modified RADAR system. The PROPHET system provides a good example of the implementation of context-aware services at construction sites. One of the issues identified is the need to improve the ability of the RADAR system to better handle indoor localization specific to construction sites (Singhvi and Terk, 2003). In addition, Anumba and Aziz (2006) have proposed a context-aware services delivery architecture which combines context-awareness and Web Services to create a pervasive environment to deliver relevant
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information that supports decision making. The proposed architecture is composed of three main components: Context Capture, Context Inference, and Context Integration. Context Capture is used to capture the context and to provide access to the system. The various dimensions of context are captured from different sources, so that current location is captured via a Wireless Local Area Network (WLAN) positioning system, for example; user device type to ensure data is delivered according to the user's device type; user identity is determined based on the unique IP address of mobile devices; user's current activity is captured through integration with a task allocation application; and time is captured via a computer clock. Context Inference provides a way to reason about the context captured by understanding the meaning of data in order to create a relationship between the services and data to be provided, as well as the context parameters. Context Integration helps in service discovery and integration, triggering pre-defined events to either push certain information to users or exchange information with other applications using Web Services in order to keep track of events on site (Anumba and Aziz, 2006). A major emphasis of the research is to make the system's functions accessible through standard Internet Protocols, independent from programming languages or operating systems, using Web Services. Table 1 summarizes and compares some of the attributes of the above two system architectures.
Table 1: Comparison between the work of Singhvi (2003) and Anumba (2006) Singhvi and Terk (2003)
Anumba and Aziz (2006)
▪
The implemented system is a practical application focusing on delivering CAD drawings, MS Word documents, and Primavera Project schedules
▪
The proposed system is a general broader model focusing on delivering relevant information to workers and PM as well as relating these changes to the company’s profile
▪
The services provided by the system allow the user to query and modify project repository
▪
The services provided by the system allow for a wider and broader range of applications, including collaboration among partners depending on the project requirements and user context under defined constraints
components
▪
System architecture consists of Client Module, Server Module, and Communication Protocol
▪
System architecture consists of 3 modules: Context Capture, Context Inference, and Context Integration
Inference
▪
Does not include a reasoning capability to draw conclusions or make decisions from the captured context
▪
A reasoning capability about the captured context is integrated in the system using a Semantic-Web model
▪
Uses a Context Module to refine context, and maps information by using XML tags
▪
Uses a Semantic-Web Model to describe context domain, and maps information using Context Broker
▪
Outdoor location is handled using GPS and indoor location is determined using modified RADAR approach
▪
Locations of mobile devices or tags are determined through WLAN positioning system
scope
Implementation
3. CONTEXT TAXONOMY The major aim of the proposed research is to deliver appropriate information that will help workers deal with the dynamics of construction (e.g., unexpected changes, material delay, and errors from the
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predecessor activities). In order to address such dynamics effectively, the dynamics of construction is viewed as the changing information of work item context (e.g., required resource delay), user context (e.g., moving around the site), and environment context (e.g., crane is passing the user’s work path), as seen in Figure 1.
environment
worker
work item
Figure 1: Capturing Construction Dynamics
Based on this view, construction context taxonomy in detail is proposed as illustrated in Figure 2. In specific, Work Item Context includes the aspects that characterize the work item on which any operation or task is being performed. This includes the identity of the work item, its schedule, required resources, and location. Furthermore, any information changing over time (e.g., schedule change and required resource delay) will be taken into account. Secondly, user context is intended to capture the user’s profile and his or her changing information by moving around the site. The user's profile is subdivided into two categories: static context and dynamic context. User Static Context includes such aspects as the user identity (e.g., name and trade) to maintain logging information and users’ role in the site (e.g., worker, foreman and supervisor) to determine required information. On the other hand, User Dynamic Context includes the location of the user relative to other users and work items, the current time and date, and the type of activity he or she is performing or supposed to be performing. This would also include how many other users are performing the same activity with the user (e.g., a carpenter working with two labourers on setting forms for a column) so that productivity measures can be calculated. Lastly, Environment Context includes such aspects as the surrounding entities (e.g., other user, work items and resources) and equipment items as well as current weather conditions. Environmental Context aims to capture the situation where the workers’ operation may be affected although there is no direct relationship between the user and the context. For example, when heavy equipments such as cranes pass through the worker’s operation area, they must be notified for safety reasons. This type of contextual information may include any entity that is not part of the current operation but could affect the execution of the task. For example, when a steel welder is performing his or her task, other workers might be close by and should be aware that welding is taking place.
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Context in Construction
Work Item
User
Environment
work item identity
current progress required resources
surrounding entities
Static User Context User user identity Context
Dynamic User Context User location Context
user role
other equipment weather conditions
time activity type
Figure 2: Construction Context Taxonomy
4. IMPLEMENTATION
In its implementation, the processing capability of the system could be performed in two ways: (1) using a processing server either on site or at the main office (e.g., mapping and reasoning between captured context and existing project information—denoted as A in Figure 3); or (2) using intelligent processing agents installed on the mobile device (denoted as B in Figure 3); therefore producing a web of agents that can communicate, process, and deliver information. In the proposed system, a particular emphasis is placed on the latter in order to capture changing situations efficiently. Context sensors capture detailed information about the different types of contextual information on sites, such as the identity of the user, the location, and activities being performed (i.e., context of work item and user). For example, the location can be captured by a WLAN positioning system, and work items can be inferred from schedule, captured location, and the user’s identity. Other surrounding entities which may affect the context of work item and user (e.g., a crane that interferes with the user’s operation on a certain item) are captured. Then, contextual information is sent to an on-site processing server where it will be analyzed, mapping and reasoning about existing information such as CAD, schedule, and specifications. This processing activity uses either central or distributed processing mechanisms. Updated information will be delivered to users through their mobile devices, perhaps PDA or helmet-mounted display screens. Users can update certain information and send it back to the server.
5. PROPOSED SCENARIOS On construction sites, where the various personnel have different roles, can benefit in several ways from the implementation of a CAC system. In this section, we present the proposed scenarios depending on the role of the user, including (1) Project Managers, (2) Foremen, and (3) Work Crews. Each of these categories can benefit from applying the CAC system in different ways. In the following subsections, we describe the proposed systems according to this hierarchy.
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Mobile Device with processing capabilities
Specification
Schedule Context Sensors used to capture context (distributed on site)
CAD
Head-mounted Displaying Device Figure 3: Implementation of Context-Aware System
5.1 Project Managers A project manager can receive on his or her mobile device several kinds of information regarding on-site material deliveries. He or she can confirm the delivery receipt of the different resources (Aziz et al., 2006), monitor delivery delays, and reschedule construction activities to accommodate any changes on deliveries. Moreover, in the case of an equipment item on-site breakdown, the project manager receives an immediate notification of the equipment type, anticipated delay due to the breakdown, and available alternatives that can be employed in order to resolve the problem. Modifying construction schedules to accommodate changes occurring on the site is a common activity that a project manager is continuously involved in. Having such information immediately as the events occur helps the project manager to keep continuous control over the project schedule and then to act accordingly. The CAC system helps to achieve this goal by providing up-to-date contextual information that can be incorporated into the project schedule. 5.2 Foremen Foremen who manage work crews and have direct contact with work activities can receive important notifications on their mobile devices through the use of the CAC system. Productivity and availability information is delivered to the on-site foreman. He or she can use this information to plan the work to be performed the next day. Any material or labour requirements can be communicated to the foreman by any crew member, making it more efficient to supply shortfalls in material or labour requirements for that particular activity. In addition, the CAC system can assist in the monitoring of the number of workers coming to the site each day. When workers enter the construction site, they will be automatically logged on to the system and their arrival time recorded. This will help in monitoring daily attendance of workers in a precise manner and will translate to a savings in effort and time compared to performing the task manually.
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Another possible application of a context-aware system is in monitoring the usage of hand and power tools, which at times can incur considerable overhead costs for the company. Each hand tool is equipped with a sensor to monitor its usage and predict requirements for maintenance or replacement. Whenever a hand tool is used, its time of usage is recorded and the supervisor is informed about the anticipated need to replace the tool or perform a routine maintenance. 5.3 Work Crews Work crews enjoy the greatest benefit of the application of the CAC system. As work crews are logged on to the system upon their arrival on site, they receive a list of the tasks and activities they are to perform on that day. They receive material requirements for a given task as well as recommended methods to perform the task, which is accompanied by relevant drawings and specifications. Furthermore, the CAC system allows work crews to efficiently deal with uncertainties and the discrepancy between as-planned and as-built through the aforementioned intelligent processing agents (B in Figure 3). Any new information will be provided as a near real-time basis, and possible coordination with other crews and foremen will be facilitated. Another important aspect of CAC has to do with safety. The proposed generic framework explicitly captures objects within the worker’s surrounding environment, such as other equipment that may be passing through the worker’s path of operation. This will greatly improve worker safety by notifying possible dangers.
6. CONCLUSION Field work in construction requires extensive information. In particular, the rapidly changing construction situations necessitate intelligent information delivery to on-site workers. Focusing on this issue, a CAC system is proposed as an innovative human-machine interaction system for construction field work. To address dynamic situations effectively, construction context taxonomy has been developed, and implementation and construction scenarios which might benefit from the application of a CAC system have been proposed. Small-scale experiments to validate the physical requirements of the system and the design of real-world scenarios for actual application are currently underway.
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